Understanding Robotics
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Understanding Robotics
Understanding Robotics is an introductory text on robotics and covers topics ranging from from the components of a robotic system, including sensors, to the industrial applications of robotics. The major factors justifying the use of robots for manufacturing are also discussed, along with the use of robots as a manufacturing tool, their impact on people, and the future of robotics. This book is comprised of eight chapters and begins with an overview of the roots of robotics and the use of robots in the manufacturing environment; advances in robot technology and typical applications of robots; reasons for using robots in the manufacturing environment; and the different manufacturing functions they perform, including visual inspection and intricate welding operations. A definition of the word ""robot"" is presented, and the impact of robots on jobs is considered. Subsequent chapters focus on the elements of a robot system, including the computer/controller, actuator power drive, and sensors; sensor applications in robotics; robotic usage by industry; economic justification of robotics; manufacturing technology and the role robotics can play in improving the United States' competitive manufacturing position; and the impact of robots on people and vice versa. The final chapter is devoted to market trends and competitiveness of the U.S. robotics industry and assesses the future prospects of robotics. This monograph should be a valuable resource for technologists and researchers interested in robots and robotics.
Understanding Robotics Control Systems
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Natural Language Understanding and Cognitive Robotics
In the not so distant future, we can expect a world where humans and robots coexist and interact with each other. For this to occur, we need to understand human traits, such as seeing, hearing, thinking, speaking, etc., and institute these traits in robots. The most essential feature necessary for robots to achieve is that of integrative multimedia understanding (IMU) which occurs naturally in humans. It allows us to assimilate pieces of information expressed through different modes such as speech, pictures, gestures, etc. The book describes how robots acquire traits like natural language understanding (NLU) as the central part of IMU. Mental image directed semantic theory (MIDST) is its core, and is based on the hypothesis that NLU is essentially the processing of mental image associated with natural language expressions, namely, mental-image based understanding (MBU). MIDST is intended to model omnisensory mental image in human and to afford a knowledge representation system in order for integrative management of knowledge subjective to cognitive mechanisms of intelligent entities such as humans and robots based on a mental image model visualized as ‘Loci in Attribute Spaces’ and its description language Lmd (mental image description language) to be employed for predicate logic with a systematic scheme for symbol-grounding. This language works as an interlingua among various kinds of information media, and has been applied to several versions of the intelligent system interlingual understanding model aiming at general system (IMAGES). Its latest version, i.e. conversation management system (CMS) simulates MBU and comprehends the user’s intention through dialogue to find and solve problems, and finally, provides a response in text or animation. The book is aimed at researchers and students interested in artificial intelligence, robotics, and cognitive science. Based on philosophical considerations, the methodology will also have an appeal in linguistics, psychology, ontology, geography, and cartography. Key Features: Describes the methodology to provide robots with human-like capability of natural language understanding (NLU) as the central part of IMU Uses methodology that also relates to linguistics, psychology, ontology, geography, and cartography Examines current trends in machine translation